353results about How to "Improve dynamic performance" patented technology

The invention relates to the technical field of storage equipment management, in particular to an intelligent control method and system for storage equipment, and aims to solve the problems of task allocation, path optimization and equipment collaboration in a complex storage scene. According to the method, a storage equipment function model comprising an upper-layer frame model and a lower-layer equipment model is constructed, task allocation and path planning are optimized by using a neural network model in combination with task requirements, and a storage equipment control instruction is generated. In the task execution process, task priorities and path planning are adjusted in real time to adapt to dynamic environment changes, and it is ensured that tasks are completed efficiently. According to the method, a task distribution diagram and a path planning scheme are further optimized through a dynamic task diagram and a dynamic energy field, the problems of equipment congestion, too high energy consumption and task delay are effectively solved, the collaboration efficiency and the resource utilization rate of storage equipment are improved, and the method is suitable for various complex storage scenes.

The invention discloses a three-phase permanent magnet synchronous motor full-speed-domain driving control system and a control method thereof. The system is composed of a torque limiting module, a full-speed-domain control neural network module, a current control module, a coordinate transformation module-I, a coordinate transformation module-II, a coordinate inverse transformation module, an SVPWM module, a SiC MOSFET driving module, a full-speed-domain position rotating speed observation module, a weak magnetic feedback module and a three-phase permanent magnet synchronous motor. The control method is used for driving the control system. According to the method, accurate tracing of the optimal dq-axis reference current working point is realized based on deep learning, and accurate control of three operation modes of MTPA, field weakening control and MTPV is realized; an improved mobile vision field estimation algorithm is adopted, and the rotor position and the rotor rotating speed are accurately estimated within the full-speed domain range; the SiC MOSFET is used as an inverter switching tube, and a brand new drive circuit is designed to adapt to the operation condition of the electric vehicle.

The invention relates to a dynamic analysis optimization method for a high-speed stamping hybrid mechanism with a lubricating gap and considering an impact load. The dynamic analysis optimization method comprises the following steps: S1, defining structural parameters and design parameters; s2, establishing a lubrication gap motion model, a contact force model and an oil film bearing force model; s3, introducing a flexible beam unit model; s4, the relative motion state of the bearing and the shaft at the revolute pair element is judged; s5, establishing a kinetic equation; s6, solving the kinetic equation; s7, optimizing and improving the structural parameters of the mechanism; and S8, circulating the above process, and carrying out iterative solution until the kinetic analysis and parameter optimization are completed. The established rigid-flexible coupling kinetic equation containing the lubricating gap can more accurately predict the mechanism dynamic response characteristics of the high-speed stamping hybrid mechanism when the high-speed stamping hybrid mechanism is subjected to the impact load in actual work and operation, and the modeling method is suitable for dynamic response characteristic analysis and optimization design of high-speed stamping mechanisms of other configurations. The method has the advantages of wide applicability and the like.

The invention discloses a modeling method of a fractional order LC type three-phase inverter, and relates to the technical field of modeling and control of power electronic converters. On the basis of a traditional integer order LC type three-phase inverter, an integer order LC type filter in the inverter is replaced by a fractional order LC type filter, so that a new fractional order inverter topology is constructed. On the basis of the topology, mathematical models under a three-phase static abc coordinate system and a two-phase rotating dq coordinate system are constructed. Based on the mathematical model, a voltage and current double-closed-loop decoupling control strategy of the fractional order LC type three-phase inverter is deduced. In addition, a traditional virtual synchronous generator control link is replaced by an FOVSG control link, and the stability of the FOVSG control link is analyzed through a small signal model. According to the invention, dynamic decoupling can be effectively realized according to the order of the fractional order LC filter. In addition, an adjustable order is introduced in the FOVSG control link, and the performance of the inverter is improved under different control requirements.

The invention provides a thick electrode and a preparation method thereof, and a lithium battery, the thick electrode comprises a current collector and an active coating, the active coating comprises an active material, a conductive agent, a dispersant and a composite binder, the composite binder comprises a binder A and a binder B, the binder A comprises at least two of sodium carboxymethyl cellulose, a polyacrylic acid binder and an acrylonitrile multipolymer, and the binder B comprises at least one of polytetrafluoroethylene and butadiene styrene rubber. The thick electrode has the characteristics of stable structure, good conductivity and high ion transmission efficiency, and the cycling stability of the battery using the thick electrode can be improved.

The invention discloses a switching loss optimization control method and system of an energy storage DC converter. Comprising the following steps: firstly, acquiring battery side voltage / current and bus side voltage / current of the energy storage direct current converter; calculating according to the battery side voltage and the bus side voltage to obtain the voltage ratio of the two sides of the energy storage direct current converter; then, control power is obtained through calculation according to the battery side voltage / current and the bus side voltage / current; then, determining the working mode of the dual-active bridge circuit by using the control power of the energy storage direct-current converter; and finally, according to the working mode of the dual-active bridge circuit, the actual power of the dual-active bridge circuit is adjusted, and the switching loss optimization of the energy storage DC converter is completed. When the battery side voltage, the bus side voltage and the load power of the circuit are changed, the control power of the controller can be continuously changed, smooth transition is realized among all working modes, the output signal and the power gain are basically linear, and the dynamic response speed can be improved.

The invention provides an ultrahigh-nickel single-crystal positive electrode material and a preparation method and application thereof.The ultrahigh-nickel single-crystal positive electrode material comprises fluxing agent doping elements and high-valence doping elements, the fluxing agent doping elements comprise Zr, Ce, Sr, Y, La, Sn or Na, and the high-valence doping elements comprise Sb, W, Nb, Ta, Mo, Ti or P; the doping amount of the fluxing agent doping element is omega A, the doping amount of the high-valence doping element is omega B, and omega A and omega B meet the following relational expression: 0.5 < 0.746 * exp [-omega B / (0.891 * omega A)] + 0.556 < 1.0. Omega A and Omega B meet a specific relational expression, two doping elements are effectively promoted to play a role, a small-particle-size and uniformly-dispersed single crystal is formed, the material has high stability and safety of the single crystal, a Li < + > diffusion path can be shortened, dynamics can be improved, and the advantage of high capacity can be achieved.

The invention discloses a USV rotary column stabilization control system considering complex disturbance and motor dynamic characteristics, belongs to the field of motion control systems of ocean mobile observation platforms, and aims to improve the stability and control efficiency of USV navigation. The method comprises the following specific steps: firstly, establishing a rotary column stabilizer lift model, a USV nonlinear rolling model and a servo motor dynamic model; then designing a Backstepping controller based on a differential item disturbance observer, estimating and compensating disturbance caused by external and model uncertainty in real time, then adjusting expected control input in real time, and ensuring that the output rolling angle tracks the expected rolling angle. The MPC controller based on servo motor state feedback is designed, the state quantity of the motor is fed back to the controller for prediction and adjustment, the problems of response lag and output overload of the servo motor in complex sea conditions are effectively solved, rolling angle error minimization and effective control over energy consumption are further achieved, and the service life of the servo motor is prolonged. And the purpose of multi-objective optimization is achieved.

The invention discloses a control algorithm of a photovoltaic energy storage inverter system, which belongs to the technical field of photovoltaic energy storage, and comprises the steps of combining PPO deep reinforcement learning, dynamically optimizing a grid-connected control strategy of an inverter by adaptively adjusting a virtual inertia and a damping coefficient, and simultaneously compensating disturbance in the system in real time by utilizing LADRC. According to the method, the robustness and the stability of the system under the complex power grid working condition are ensured, the technical problem of improving the robustness, the dynamic response capability and the grid-connected control precision of the photovoltaic energy storage inverter system is solved, the flexibility of the system is improved, the dynamic performance of the system under the non-linear interference condition is improved, and the reliability of the system is improved. The stability and robustness of the system are maintained, and the reliability and stability of the whole grid-connected process are also significantly improved.

The invention relates to the technical field of grid-connected inverter control, and discloses a grid-connected inverter model predictive control method based on a neutral-point potential fluctuation control factor, in the process of controlling a grid-connected inverter by using model predictive control, firstly, an SVPWM method and the model predictive control method are combined, the design of an objective function is simplified, and the model predictive control factor is optimized; the optimal switch sequence can be selected only by calculating the midpoint potential deviation; secondly, neutral-point potential balance control is realized in spatial modulation, a large sector is further divided into a plurality of small sectors, the position of the small sector where a reference voltage vector is located is determined, a switch sequence is selected from the determined small sectors for traversal, the traversal frequency is reduced, and the calculation efficiency is improved; and finally, designing a midpoint potential control factor, and greatly reducing the content of high-amplitude common-mode voltage on the premise of ensuring the balance of the midpoint potential. Moreover, the overall control structure is clear and easy to implement, and the dynamic performance and the steady-state tracking performance of the controller are both improved.

The invention provides a method and a device for realizing cross-network equipment authentication in a distributed soft bus, and belongs to the field of encrypted communication. The method comprises the following steps: in a local area network, equipment configures an authentication mode, a central node address and an authentication strategy of an authentication list according to different service scenes to realize authentication; for a cross-network scene, the leaf node realizes cross-network authentication through the proxy node, specifically, the leaf node and the proxy node in a local area network where the leaf node is located are authenticated; cross-network authentication is carried out among the proxy nodes in different local area networks through a Hichain module based on a distributed soft bus; after the authentication of the two levels is completed, trust is considered to be established between the leaf nodes; and cross-network communication is carried out among the leaf nodes through a key rate generated by one-time mask encryption. According to the scheme, the limitation that the existing distributed soft bus technology is only limited to equipment authentication in a local area network is broken through, and safety authentication between cross-network equipment is realized.

The invention relates to a district and county level power industry carbon emission prediction method based on power carbon traceability. The method comprises the following steps: carrying out user side load prediction in different areas and time periods; carrying out distributed power supply output prediction in different regions and different time periods; performing energy storage charging and discharging scheme prediction and source side carbon emission factor prediction; carrying out load flow calculation on each node in different regions and time periods; constructing a power matrix; measuring and calculating a single-time-point carbon emission index; and measuring and calculating the long-time scale carbon emission. According to the method, prediction data of user power utilization, clean energy power generation and energy storage charging and discharging are integrated, the carbon emission measurement and calculation requirements of different time periods and regions can be met, the applicability and flexibility of the model are enhanced, accurate prediction of the carbon emission in the whole power distribution network load storage link can be achieved, and the accuracy of carbon emission measurement and calculation is improved; the method particularly focuses on the influence of policy changes of an electric vehicle, a distributed power supply and the like on the carbon emission, so that the prediction result can reflect actual changes brought by the policy changes.

The invention relates to an inertial navigation / polarization compass / laser velocimeter integrated navigation method, which belongs to the technical field of inertial navigation / integrated navigation, and comprises the following steps: mounting and fixing an inertial navigation system, a polarization compass and a laser velocimeter on a carrier, and acquiring coordinate systems of sensors; establishing a polarization compass error equation and a laser velocimeter error equation by considering a course angle installation error, a pitch angle installation error and a scale error of the laser velocimeter; and deriving an inertial navigation / polarization compass / laser velocimeter combined system state equation based on the error equation, establishing a measurement equation by taking the difference between the speed calculated by inertial navigation and the speed of the laser velocimeter and the product of the polarization vector of the polarization compass and the sun vector as observed quantities, and carrying out estimation and feedback correction on the system state. The invention provides an inertial navigation / polarization compass / laser velocimeter combined navigation method in a satellite navigation denial environment, which realizes full-autonomous and high-precision directional positioning.

The invention belongs to the technical field of hypersonic flight vehicle control, and relates to an intelligent control method for a hypersonic flight vehicle driven by coupling information. Firstly, a longitudinal dynamic model of the elastic hypersonic aircraft is established; then, a coupling database based on sampling analysis is constructed, different flight envelope data are simulated, a coupling degree matrix is calculated through a sampling statistical algorithm, and the coupling database is formed to quantify the mutual influence between variables; furthermore, deep neural network training driven by coupling data is carried out, a long-short term memory network is adopted, and a coupling database is used as a data sample to carry out offline training, so that the autonomous fine control capability of the aircraft in a strong coupling environment is improved. And finally, designing an online controller to realize a coupling information intelligent compensation scheme, dividing aircraft maneuvering control into a speed loop and an attitude loop, and designing a corresponding control instruction and a neural network updating law to realize real-time and intelligent flight control.

The invention discloses a preparation method of a phosphorus-doped hard carbon composite material for a sodium battery. The preparation method comprises the following steps: preparing a hard carbon precursor, preparing a phosphorus-doped precursor, preparing a catalyst precursor, preparing a hard carbon composite material, and carrying out pickling purification. Through pre-oxidation treatment on the biomass raw material, oxygen-containing free radicals can be introduced, the structural disorder can be improved, the sodium storage space and the capacity can be improved, phosphorus elements are uniformly distributed into the hard carbon material through a vapor deposition method, meanwhile, graphene and carbon nanotubes are formed in the material, closed pores are increased, the sodium storage space is improved, and the performance of the hard carbon material is improved. According to the present invention, the ion transmission path is shortened, the sodium ion transmission is accelerated, the capacity and the conductivity of the material are enhanced, the material is coated with the amorphous carbon formed by the asphalt, such that the phosphorus expansion can be inhibited, the contact with the electrolyte can be avoided, the capacity and the first effect can be improved, and the phosphorus and the coating layer can be re-distributed while the asphalt coating is performed so as to form the small amount of the phosphorus fiber crystal; and the conductivity and the capacity are improved.

The invention provides an intelligent inventory management method, device and equipment and a storage medium, and the method comprises the steps: carrying out the data collection and preprocessing of an enterprise resource planning system, a supplier management system and a point-of-sale system of a target enterprise, obtaining an integrated data set, constructing a plurality of time-varying autoregression demand prediction models, and carrying out the prediction of the demands of the target enterprise. Combining a plurality of prediction results for constructing a plurality of time-varying autoregression demand prediction models in combination with an ensemble learning method to obtain a dynamic demand prediction result; according to the deep Q network model, evaluating an inventory replenishment decision in combination with the dynamic demand prediction result and the integrated data set to obtain an inventory optimization strategy; and performing multi-target Pareto optimization on the inventory management of the target enterprise according to the inventory optimization strategy to obtain and execute an intelligent inventory management scheme. According to the method, the comprehensiveness and the dynamism of demand prediction are remarkably improved by comprehensively utilizing data of all systems in an enterprise and applying an advanced time-varying prediction model and an integrated learning technology.

The invention discloses a synchronous motor sensorless control method based on a Newton-Raphson predictive phase-locked loop, and relates to the technical field of motor control. The invention aims to solve the problems that an existing position-sensorless control method is limited by extra loss and noise caused by high-frequency signal injection in the aspect of position signal extraction and poor dynamic performance caused by a traditional phase-locked loop technology, and a prediction phase-locked loop technology needs a large amount of iterative operation for solving a cost function. According to the method, the flux linkage estimation value of the alpha-beta coordinate system is observed, the filtered flux linkage estimation value of the alpha-beta coordinate system is reconstructed, and then a cost function is constructed; when the number of iterations in the current motor control period does not reach the maximum, updating a rotor position angle by using a Newton method, and further updating a cost function; and when the number of iterations in the current motor control period reaches the maximum, calculating a convergence angle in the current motor control period by using an improved Newton method, and calculating an angular velocity estimated value, thereby realizing position-sensorless control of the synchronous motor.

The invention relates to the technical field of off-grid photovoltaic disturbance rejection, in particular to a method for enhancing off-grid photovoltaic disturbance rejection capability based on an intelligent filtering technology. Firstly, known disturbances such as illumination, temperature and load abrupt change in the system are analyzed, and a model is established. Designing an intelligent filter, monitoring and estimating unknown disturbance by using a self-adaptive algorithm, obtaining direct current and harmonic disturbance observation values, and fusing the direct current and harmonic disturbance observation values; and then an active disturbance rejection controller based on intelligent filtering is constructed, unknown disturbance and known disturbance are added to obtain a concentrated disturbance observation value, and parameters are designed to respond to suppression disturbance. And finally, obtaining a voltage preliminary control instruction, and combining with a filter observation value construction instruction to suppress current harmonic disturbance. Through the steps, the stability and reliability of the off-grid photovoltaic system are improved.

The invention provides an infusion flow rate control optimization method based on improved PID (Proportion Integration Differentiation), which belongs to the field of PID control optimization and comprises the following specific steps: S1, acquiring key operation data in an infusion process by utilizing a real-time monitoring device; s2, dynamically matching the infusion flow rate change trend monitored in the infusion process with the response of the control system to generate an infusion flow rate error; s3, the infusion flow velocity error is input into an improved infusion flow velocity PID controller, and an infusion pump control signal is output; s4, according to the specific implementation of the improved infusion flow rate PID controller, the optimal control parameters of the infusion flow rate PID controller are obtained through iterative optimization of an improved simulated cooking training algorithm; the improved simulated cooking training algorithm comprises the following steps: S41, introducing a dynamic inertia weight; s42, using a global information transmission mechanism; s5, the infusion pump control signal is used for controlling the speed of an infusion pump, and accurate and stable control over the infusion flow speed is achieved.

The invention belongs to the related technical field of robots, and discloses a leg structure assembly of a humanoid robot and the humanoid robot, and the leg structure assembly comprises a hip joint assembly and a leg structure assembly, the hip joint assembly comprises three driving modules, and three-degree-of-freedom rotation movement similar to human hips is achieved; the knee joint assembly comprises a knee joint structure, a knee joint driving module and a knee joint transmission assembly, the knee joint driving module is installed at the upper end of the thigh structure, and the knee joint transmission assembly drives the shank structure to bend and stretch; the ankle joint assembly comprises an ankle joint structure, an ankle joint driving module and an ankle joint transmission assembly, the ankle joint driving module is installed at the upper end of the thigh structure and located below the knee joint driving module, and the ankle joint transmission assembly drives the foot structure to achieve plantar flexion / dorsiflexion movement and extroversion / adduction movement. The driving modules are moved upwards to the upper ends of the thigh structures, and the humanoid robot has the advantages of being free of driving modules at the tail ends, concentrated in mass and small in rotational inertia, and the movement frequency of the humanoid robot can be improved.

The invention relates to the technical field of vibration sensors, and discloses a miniaturized digital vibration sensor, which comprises a shell, one side of the shell is connected with a shell cover, and one side of the shell cover is provided with a detection assembly for detecting vibration; the detection assembly comprises a shielding seat and a connecting rod, one side of the top of the shielding seat is provided with a magnet, and the top of the magnet is provided with a magnetic core; a coil sleeving the outer side of the magnetic core is adhered to the bottom of the connecting rod; a ruby in contact with a to-be-detected object is fixed at the top of the connecting rod; the inner wall of the shell cover is in threaded connection with a pressing ring, the top of the pressing ring is connected with a second spring piece, the top of the second spring piece is connected with a supporting frame, when vibration is generated through rotation of the bearing, the ruby makes contact with an outer ring of the bearing and transmits the vibration to the connecting rod, and the connecting rod drives the coil to move on the outer side of the magnetic core, cuts magnetic lines of force and generates induction voltage. The electromagnetic induction principle ensures that a vibration signal can be accurately converted into an electric signal, so that high-precision vibration measurement is realized.

The invention discloses a negative pole piece and a lithium ion battery, belongs to the technical field of lithium ion batteries, and overcomes the defects that the rate capability of the lithium ion battery in the prior art is relatively low, and lithium is easy to separate out in a circulating process. The negative electrode active material comprises a first negative electrode active material and a second negative electrode active material, the negative electrode active material satisfies the following conditions: A-B = 0.01-0.75 g / cm < 3 >; a is the ultimate compaction density of the first negative electrode active material, and B is the ultimate compaction density of the second negative electrode active material; in the negative electrode active material layer, the negative electrode active material layer comprises n coating layers along the direction far away from the current collector, n is more than or equal to 3 and less than or equal to 10, and n is an integer; along the direction far away from the current collector, the content of the first negative electrode active material in the n coating layers is gradually reduced, and the content of the second negative electrode active material is gradually increased. The problem of local black spots or lithium precipitation of the anode interface can be avoided, and meanwhile the cycling stability is improved.

The invention relates to a multi-shaft compressor unit and a control method thereof, in particular to a steam-electricity double-drive multi-shaft compressor unit connected with double clutches and a control method of the steam-electricity double-drive multi-shaft compressor unit. The technical problems that in the prior art, a pure electricity mode, a pure steam mode and a steam-electricity double-drive mode cannot be switched on line, and when steam is sufficient, a motor cannot be disengaged, so that energy is wasted are solved. The system comprises a multi-shaft compressor, a steam turbine, a motor, a first clutch, a second clutch, a steam flow sensor, a controller and a rotating speed sensor. The multi-shaft compressor comprises a driving shaft; the driving shaft is provided with two driving ends which are respectively a first driving end and a second driving end; the output shaft of the steam turbine is coaxially connected with the first driving end through a first clutch; an output shaft of the motor is coaxially connected with the second driving end through the second clutch; and rotating speed sensors are arranged on the first driving end, the second driving end, the steam turbine and the output shaft of the motor.

The invention provides an air conditioning system energy consumption simulation method and device based on data driving, and the method comprises the steps: firstly collecting the real-time data of a water chilling unit, a chilled water pump, a cooling water pump, a cooling tower and a tail end air conditioner in the operation process of an air conditioning system in parallel; the real-time data of the water chilling unit, the chilled water pump, the cooling water pump, the cooling tower and the tail end air conditioner are subjected to multiple regression fitting, and a water chilling unit energy consumption model, a cooling water pump energy consumption model, a chilled water pump energy consumption model, a cooling tower energy consumption model and a tail end air conditioner energy consumption model are obtained; fitting the fitting power in the energy consumption model again to obtain an air-conditioning system energy consumption model, and finally simulating the operation energy consumption of the air-conditioning system under the corresponding working condition by adopting the air-conditioning system energy consumption model under the given operation working condition of the air-conditioning system. According to the method, the problem that the simulation power result is inaccurate due to poor dynamic property and time-varying property of the existing simulation model is solved.

The invention discloses a backstepping active-disturbance-rejection control method and device for a permanent magnet synchronous motor and a medium, and relates to the field of motor control. The invention aims to solve the problem of overshoot in the control process of the traditional three-phase motor. The invention relates to a backstepping active-disturbance-rejection control method for a permanent magnet synchronous motor. The method comprises the following steps: constructing a permanent magnet synchronous motor second-order dynamics simplified model with an error disturbance factor; de-noising the model by using a differential tracker; observing the denoised model by using a first-order extended state observer; obtaining an error disturbance factor of the motor control system by using a nonlinear state error feedback control law based on the observation result, and compensating the error disturbance factor to obtain external disturbance of the motor control system after compensation; and designing a backstepping controller of the permanent magnet synchronous motor by adopting a backstepping method on the basis of the compensated external disturbance of the motor control system, obtaining a control quantity by utilizing the backstepping controller of the permanent magnet synchronous motor, and further controlling a rotating speed ring in vector control of the permanent magnet synchronous motor.

The application provides a double-motor driving and rigidity actively adjustable series elastic actuator and a control method thereof, which utilizes elastic elements to convert kinetic energy and potential energy, reduces system energy consumption, improves system energy utilization efficiency, improves dynamic performance of the actuator by introducing the elastic elements, strengthens the anti-impact capability of the system, and improves the safety of human-machine interaction; rigidity is controlled by changing the effective lever arm length between the end of the actuator and the elastic element, the deformation of the elastic element under the load of the actuator is measured, the transmission ratio of the system is calculated, the output torque is obtained, and the output force control of the actuator is further realized. The application utilizes double-motor driving and double-differential transmission mechanism to realize active adjustment of the output rigidity of the actuator system, and has a more extensive use scene and application range.

The invention relates to the field of jumping robots, in particular to a hydraulically-driven two-degree-of-freedom coupling type humanoid-leg jumping robot and a control method thereof. The overall structure of the robot simulating jumping of the human legs is composed of a driving assembly, a thigh assembly and a shank assembly. The designed jumping robot is simplified into an SLIP model, a PID controller is adopted in the jumping process to achieve control over the flying phase of the jumping robot, and a PD controller is adopted in the landing phase for control. The hydraulic cylinders are far away from the legs, so that the hydraulic cylinders are driven to move to the upper body, and the whole robot has better attractiveness. And meanwhile, the lightweight design of the legs is achieved, the inertia of the legs is reduced, and the robot has more stable dynamic performance. And the vertically placed hydraulic cylinder is designed, so that the driving efficiency is further improved, and finally, more efficient bionic jumping movement is realized.

The invention provides a rail train traction and brake control method and system, and the method comprises the steps: firstly monitoring the wheel rotation speed and motor torque of a rail train, inputting a state observer with pole configuration to estimate an adhesion coefficient in real time, and combining the creep speed at the current moment to obtain a traction and brake coefficient; calculating the stick-slip slope of the adhesion characteristic curve by using an adhesion coefficient-creep speed empirical formula; the method comprises the following steps: setting a target creep speed by adopting a steepest gradient method, inputting the target creep speed and a current creep speed into a neural network controller, outputting a rail train correction torque, combining the rail train correction torque with a current actual braking torque to obtain a target torque, and controlling a rail train motor through a DTC method so that the actual torque is consistent with the target torque. And the motor torque and the wheel speed are input into the state observer to form closed-loop control. The adhesion coefficient is estimated and optimized in real time through the control method, the train traction and braking efficiency is remarkably improved, and a safer and more efficient solution is provided for modern rail transit.

The invention provides a resonance suppression method for a three-phase PWM (Pulse Width Modulation) rectifier with an LCL (Lower Control Limit) filter, which relates to a three-phase PWM rectifier control technology, and is characterized in that on the basis of vector control of power grid voltage orientation, voltage and current sampling is carried out at fixed time intervals, inner loop control is implemented, and on the premise of ensuring volt-second balance in a pulse width modulation process, namely, a PWM process, the voltage and current are sampled at fixed time intervals, so that the resonance suppression efficiency is improved. And the sampling period is minimized. According to the method, the sampling frequency is increased, the system bandwidth is improved, and resonance suppression can be achieved under the low carrier frequency when main circuit parameters are not matched.

The invention discloses an active power filter control method and system suitable for frequency fluctuation, and the method employs an FIR filter based on a Lagrange interpolation method to correct the decimal part of the sampling times, and employs a variable bandwidth adjustment internal model control (VBAI) technology to improve the bandwidth after frequency fluctuation. The problem that the control effect is seriously reduced due to the fact that traditional repeated control sampling times change caused by power grid frequency fluctuation is effectively solved, and control gain stability under frequency fluctuation is guaranteed.